Introduction: The purpose of this study was to demonstrate the effectiveness of the TGS calculation method to identify genetic athletic predisposition in two groups of basketball and soccer players based on genetics analysis. Through the genetic profile we calculated, by an algorithm, the TGS (Total Genetic Score) in both groups; this idea comes from the concept that it's better to personalized workout based on athlete genetic profile. Identifying specifically performance demands (based on the metabolism system used during performance, aerobic or anaerobic) and paying attention to the performance- enhancing genes and their polymorphisms, is important focus it in order to build personalized and successful training for every single athlete. Materials and methods: We considered two groups of professional athletes: 21 basketball players and 21 soccer players both involved in professional championships. For the genetic analysis a saliva sample was taken from athletes, and the polymorphisms were analysed: ACE; ACTN3; CK-MM; PPARα PPARγC1; NRF2 A/G; NRF2 C/T. Each genotype was scored from 0 to 2 depending on whether they were more related to resistance or power activity. The sum of these scores generates the total TGS for each athlete and was compared both for resistance and power. Results: Our results indicate that professional basketball players have a power-related TGS higher than the resistancerelated conversely the football players, that have a resistance-related TGS greater than power-related one. Conclusion: TGS can be a useful tool to identify the genetic predisposition of the athlete starting from the genetic analysis of some PEPs, regardless of the type and number of genes analysed.

Total genetic score: An instrument to improve the performance in the elite athletes

Amato A.;
2018-01-01

Abstract

Introduction: The purpose of this study was to demonstrate the effectiveness of the TGS calculation method to identify genetic athletic predisposition in two groups of basketball and soccer players based on genetics analysis. Through the genetic profile we calculated, by an algorithm, the TGS (Total Genetic Score) in both groups; this idea comes from the concept that it's better to personalized workout based on athlete genetic profile. Identifying specifically performance demands (based on the metabolism system used during performance, aerobic or anaerobic) and paying attention to the performance- enhancing genes and their polymorphisms, is important focus it in order to build personalized and successful training for every single athlete. Materials and methods: We considered two groups of professional athletes: 21 basketball players and 21 soccer players both involved in professional championships. For the genetic analysis a saliva sample was taken from athletes, and the polymorphisms were analysed: ACE; ACTN3; CK-MM; PPARα PPARγC1; NRF2 A/G; NRF2 C/T. Each genotype was scored from 0 to 2 depending on whether they were more related to resistance or power activity. The sum of these scores generates the total TGS for each athlete and was compared both for resistance and power. Results: Our results indicate that professional basketball players have a power-related TGS higher than the resistancerelated conversely the football players, that have a resistance-related TGS greater than power-related one. Conclusion: TGS can be a useful tool to identify the genetic predisposition of the athlete starting from the genetic analysis of some PEPs, regardless of the type and number of genes analysed.
2018
Basketball
Genetics analysis
Performance demands
Polymorphisms
Soccer
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/633089
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